Ultrafine Particle Number Concentration Model for Estimating Retrospective and Prospective Long-Term Ambient Exposures in Urban Neighborhoods

Source apportionment of ultrafine particles in urban Europe

There is a body of evidence that ultrafine particles (UFP, those with diameters ≤ 100 nm) might have significant impacts on health. Accordingly, identifying sources of UFP is essential to develop abatement policies. This study focuses on urban Europe, and aims at identifying sources and quantifying their contributions to particle number size distribution (PNSD) using receptor modelling (Positive Matrix Factorization, PMF), and evaluating long-term trends of these source contributions using the non-parametric Theil-Sen's method. Datasets evaluated include 14 urban background (UB), 5 traffic (TR), 4 suburban background (SUB), and 1 regional background (RB) sites, covering 18 European and 1 USA cities, over the period, when available, from 2009 to 2019. Ten factors were identified (4 road traffic factors, photonucleation, urban background, domestic heating, 2 regional factors and long-distance transport), with road traffic being the primary contributor at all UB and TR sites (56-95 %), and photonucleation being also significant in many cities. The trends analyses showed a notable decrease in traffic-related UFP ambient concentrations, with statistically significant decreasing trends for the total traffic-related factors of -5.40 and -2.15 % yr-1 for the TR and UB sites, respectively. This abatement is most probably due to the implementation of European emissions standards, particularly after the introduction of diesel particle filters (DPFs) in 2011. However, DPFs do not retain nucleated particles generated during the dilution of diesel exhaust semi-volatile organic compounds (SVOCs). Trends in photonucleation were more diverse, influenced by a reduction in the condensation sink potential facilitating new particle formation (NPF) or by a decrease in the emissions of UFP precursors. The decrease of primary PM emissions and precursors of UFP also contributed to the reduction of urban and regional background sources.

Airborne ultrafine particle concentrations and brain cancer incidence in Canada's two largest cities

BACKGROUND

Malignant brain tumours are rare, but are important to study because survival rates are low and few modifiable risk factors have been identified. Existing evidence suggests that outdoor ultrafine particles (UFPs; particulate matter < 100 nm; sometimes referred to as nanoparticles) can deposit in the brain and could encourage initiation and progression of cancerous tumours, but epidemiological data are limited.

METHODS

High-resolution estimates of outdoor UFP concentrations and size were linked to residential locations of approximately 1.5 million people in Montreal and Toronto, Canada from 2001 to 2015. Cox proportional hazards models were used to estimate associations between annual average outdoor UFPs and malignant brain tumour incidence while adjusting for potential confounding factors including other outdoor air pollutants.

FINDINGS

In total, 1365 incident brain tumour cases occurred during follow-up. Consistent positive associations were observed between long-term exposures to outdoor UFPs and brain tumour incidence with increased risk ranging from 10.5% (95% CI: -1.4, 24.0%) to 15.3% (95% CI: 0.4, 32.5%) per 10,000 particle/cm3 increase. Long-term exposures to oxidant gases, black carbon, or fine particulate matter (PM2.5) were not associated with increased brain tumour incidence.

INTERPRETATION

Our results suggest that long-term exposures to outdoor UFPs are associated with an increased risk of developing malignant brain tumours. On an absolute scale, the magnitude of this risk translates into approximately 24 additional cases per year per 10,000 particle/cm3 increase in annual average outdoor UFPs in a hypothetical city of 3-million people.

FUNDING

Canadian Institutes of Health Research (CIHR) Foundation Grant and The United States Health Effects Institute (HEI).

Inter-annual trends of ultrafine particles in urban Europe

Ultrafine particles (UFP, those with diameters ≤ 100 nm), have been reported to potentially penetrate deeply into the respiratory system, translocate through the alveoli, and affect various organs, potentially correlating with increased mortality. The aim of this study is to assess long-term trends (5-11 years) in mostly urban UFP concentrations based on measurements of particle number size distributions (PNSD). Additionally, concentrations of other pollutants and meteorological variables were evaluated to support the interpretations. PNSD datasets from 12 urban background (UB), 5 traffic (TR), 3 suburban background (SUB) and 1 regional background (RB) sites in 15 European cities and 1 in the USA were evaluated. The non-parametric Theil-Sen's method was used to detect monotonic trends. Meta-analyses were carried out to assess the overall trends and those for different environments. The results showed significant decreases in NO, NO2, BC, CO, and particle concentrations in the Aitken (25-100 nm) and the Accumulation (100-800 nm) modes, suggesting a positive impact of the implementation of EURO 5/V and 6/VI vehicle standards on European air quality. The growing use of Diesel Particle Filters (DPFs) might also have clearly reduced exhaust emissions of BC, PM, and the Aitken and Accumulation mode particles. However, as reported by prior studies, there remains an issue of poor control of Nucleation mode particles (smaller than 25 nm), which are not fully reduced with current DPFs, without emission controls for semi-volatile organic compounds, and might have different origins than road traffic. Thus, contrasting trends for Nucleation mode particles were obtained across the cities studied. This mode also affected the UFP and total PNC trends because of the high proportion of Nucleation mode particles in both concentration ranges. It was also found that the urban temperature increasing trends might have also influenced those of PNC, Nucleation and Aitken modes.

Ambient ultrafine particle (PM0.1): Sources, characteristics, measurements and exposure implications on human health

The problem of ultrafine particles (UFPs; PM_0.1) has been prevalent since the past decades. In addition to become easily inhaled by human respiratory system due to their ultrafine diameter (<100 nm), ambient UFPs possess various physicochemical properties which make it more toxic. These properties vary based on the emission source profile. The current development of UFPs studies is hindered by the problem of expensive instruments and the inexistence of standardized measurement method. This review provides detailed insights on ambient UFPs sources, physicochemical properties, measurements, and estimation models development. Implications on health impacts due to short-term and long-term exposure of ambient UFPs are also presented alongside the development progress of potentially low-cost UFPs sensors which can be used for future UFPs studies references. Current challenge and future outlook of ambient UFPs research are also discussed in this review. Based on the review results, ambient UFPs may originate from primary and secondary sources which include anthropogenic and natural activities. In addition to that, it is confirmed from various chemical content analysis that UFPs carry heavy metals, PAHs, BCs which are toxic in its nature. Measurement of ambient UFPs may be performed through stationary and mobile methods for environmental profiling and exposure assessment purposes. UFPs PNC estimation model (LUR) developed from measurement data could be deployed to support future epidemiological study of ambient UFPs. Low-cost sensors such as bipolar ion and ionization sensor from common smoke detector device may be further developed as affordable instrument to monitor ambient UFPs. Recent studies indicate that short-term exposure of UFPs can be associated with HRV change and increased cardiopulmonary effects. On the other hand, long-term UFPs exposure have positive association with COPD, CVD, CHF, pre-term birth, asthma, and also acute myocardial infarction cases.

Ambient ultrafine particles and asthma onset until age 20: The PIAMA birth cohort

RATIONALE

Evidence regarding the role of long-term exposure to ultrafine particles (<0.1 μm, UFP) in asthma onset is scarce.

OBJECTIVES

We examined the association between exposure to UFP and asthma development in the Dutch PIAMA (Prevention and Incidence of Asthma and Mite Allergy) birth cohort and assessed whether there is an association with UFP, independent of other air pollutants.

METHODS

Data from birth up to age 20 years from 3687 participants were included. Annual average exposure to UFP at the residential addresses was estimated with a land-use regression model. Overall and age-specific associations of exposure at the birth address and current address at the time of follow-up with asthma incidence were assessed using discrete-time hazard models adjusting for potential confounders. We investigated both single- and two-pollutant models accounting for co-exposure to other air pollutants (PM_2.5 and PM₁₀ mass concentrations, nitrogen dioxide, and PM_2.5 absorbance).

MEASUREMENTS AND MAIN RESULTS

A total of 812 incident asthma cases were identified. Overall, we found that higher UFP exposure was associated with higher asthma incidence (adjusted odds ratio (95% confidence interval) 1.08 (1.02,1.14) and 1.06 (1.00, 1.12) per interquartile range increase in exposure at the birth address and current address at the time of follow-up, respectively). Age-specific associations were not consistent. The association was no longer significant after adjustment for other traffic-related pollutants (nitrogen dioxide and PM_2.5 absorbance).

CONCLUSIONS

Our findings support the importance of traffic-related air pollutants for asthma development through childhood and adolescence, but provide little support for an independent effect of UFP.

Non-linear models for black carbon exposure modelling using air pollution datasets

Black carbon (BC) is a product of incomplete combustion, present in urban aerosols and sourcing mainly from road traffic. Epidemiological evidence reports positive associations between BC and cardiovascular and respiratory disease. Despite this, BC is currently not regulated by the EU Air Quality Directive, and as a result BC data are not available in urban areas from reference air quality monitoring networks in many countries. To fill this gap, a machine learning approach is proposed to develop a BC proxy using air pollution datasets as an input. The proposed BC proxy is based on two machine learning models, support vector regression (SVR) and random forest (RF), using observations of particle mass and number concentrations (N), gaseous pollutants and meteorological variables as the input. Experimental data were collected from a reference station in Barcelona (Spain) over a 2-year period (2018-2019). Two months of additional data were available from a second urban site in Barcelona, for model validation. BC concentrations estimated by SVR showed a high degree of correlation with the measured BC concentrations (R² = 0.828) with a relatively low error (RMSE = 0.48 μg/m³). Model performance was dependent on seasonality and time of the day, due to the influence of new particle formation events. When validated at the second station, performance indicators decreased (R² = 0.633; RMSE = 1.19 μg/m³) due to the lack of N data and PM_2.5 and the smaller size of the dataset (2 months). New particle formation events critically impacted model performance, suggesting that its application would be optimal in environments where traffic is the main source of ultrafine particles. Due to its flexibility, it is concluded that the model can act as a BC proxy, even based on EU-regulatory air quality parameters only, to complement experimental measurements for exposure assessment in urban areas.

Effects of inhalation frequency on inhalation/exposure dose of hazardous nanoparticles and toxic gases during cigarette smoking

In this study, we measured the pollutants generations during cigarette smoking under various inhalation frequency experiment scenarios by a self-developed smoking machine. Some concepts, the effective inhaled amount and exposure amount were proposed to quantitatively estimate emission rates. Important findings include: For interval 1 s, 2 s, 3 s, 4 s and 9 s (called from 1 s to 9 s herein), effective inhaled nano-scale PN (particle number) per cigarette was 8.43E+09 #, 7.24E+09 #, 5.74E+ 09 #, 3.82E+09 # and 1.15E+09 #, it decreased linearly with interval time; exposure amount of PN in side stream smoke was 1.06E+10 #, 1.2E+10 #, 1.48E+10 #, 1.84E+10 # and 8.74E+10 #, it increased with interval time. For toxic gases, all pollutants decreased with interval time in main stream smoke. In side stream smoke, NOx and CO firstly increased with interval time and then decreased (with the highest value at 3 s interval time), while HC always increased with interval time. So, this study is useful to understand the relationship between pollution and smoking habit.

Ultrafine particles, particle components and lung function at age 16 years: The PIAMA birth cohort study

BACKGROUND

Particulate matter (PM) air pollution exposure has been linked to lung function in adolescents, but little is known about the relevance of specific PM components and ultrafine particles (UFP).

OBJECTIVES

To investigate the associations of long-term exposure to PM elemental composition and UFP with lung function at age 16 years.

METHODS

For 706 participants of a prospective Dutch birth cohort, we assessed associations of forced expiratory volume in 1 s (FEV₁) and forced vital capacity (FVC) at age 16 with average exposure to eight elemental components (copper, iron, potassium, nickel, sulfur, silicon, vanadium and zinc) in PM_2.5 and PM₁₀, as well as UFP during the preceding years (age 13-16 years) estimated by land-use regression models. After assessing associations for each pollutant individually using linear regression models with adjustment for potential confounders, independence of associations with different pollutants was assessed in two-pollutant models with PM mass and NO₂, for which associations with lung function have been reported previously.

RESULTS

We observed that for most PM elemental components higher exposure was associated with lower FEV₁, especially PM₁₀ sulfur [e.g. adjusted difference -2.23% (95% confidence interval (CI) -3.70 to -0.74%) per interquartile range (IQR) increase in PM₁₀ sulfur]. The association with PM₁₀ sulfur remained after adjusting for PM₁₀ mass. Negative associations of exposure to UFP with both FEV₁ and FVC were observed [-1.06% (95% CI: -2.08 to -0.03%) and -0.65% (95% CI: -1.53 to 0.23%), respectively per IQR increase in UFP], but did not persist in two-pollutant models with NO₂ or PM_2.5.

CONCLUSIONS

Long-term exposure to sulfur in PM₁₀ may result in lower FEV₁ at age 16. There is no evidence for an independent effect of UFP exposure.

Prenatal Ambient Ultrafine Particle Exposure and Childhood Asthma in the Northeastern United States

Rationale: Ambient ultrafine particles (UFPs; with an aerodynamic diameter < 0.1 μm) may exert greater toxicity than other pollution components because of their enhanced oxidative capacity and ability to translocate systemically. Studies examining associations between prenatal UFP exposure and childhood asthma remain sparse. Objectives: We used daily UFP exposure estimates to identify windows of susceptibility of prenatal UFP exposure related to asthma in children, accounting for sex-specific effects. Methods: Analyses included 376 mother-child dyads followed since pregnancy. Daily UFP exposure during pregnancy was estimated by using a spatiotemporally resolved particle number concentration prediction model. Bayesian distributed lag interaction models were used to identify windows of susceptibility for UFP exposure and examine whether effect estimates varied by sex. Incident asthma was determined at the first report of asthma (3.6 ± 3.2 yr). Covariates included maternal age, education, race, and obesity; child sex; nitrogen dioxide (NO2) and temperature averaged over gestation; and postnatal UFP exposure. Measurements and Main Results: Women were 37.8% Black and 43.9% Hispanic, with 52.9% reporting having an education at the high school level or lower; 18.4% of children developed asthma. The cumulative odds ratio (95% confidence interval) for incident asthma per doubling of the UFP exposure concentration across pregnancy was 4.28 (1.41-15.7), impacting males and females similarly. Bayesian distributed lag interaction models indicated sex differences in the windows of susceptibility, with the highest risk of asthma seen in females exposed to higher UFP concentrations during late pregnancy. Conclusions: Prenatal UFP exposure was associated with asthma development in children, independent of correlated ambient NO2 and temperature. Findings will benefit future research and policy-makers who are considering appropriate regulations to reduce the adverse effects of UFPs on child respiratory health.

Predicting Within-City Spatial Variations in Outdoor Ultrafine Particle and Black Carbon Concentrations in Bucaramanga, Colombia: A Hybrid Approach Using Open-Source Geographic Data and Digital Images

Outdoor ultrafine particles (UFP, <0.1 μm) and black carbon (BC) vary greatly within cities and may have adverse impacts on human health. In this study, we used a hybrid approach to develop new models to estimate within-city spatial variations in outdoor UFP and BC concentrations across Bucaramanga, Colombia. We conducted a mobile monitoring campaign over 20 days in 2019. Regression models were trained on land use data and combined with predictions from convolutional neural networks (CNN) trained to predict UFP and BC concentrations using satellite and street-level images. The combined UFP model (R² = 0.54) outperformed the CNN (R² = 0.47) and land use regression (LUR) models (R² = 0.47) on their own. Similarly, the combined BC model also outperformed the CNN and LUR BC models (R² = 0.51 vs 0.43 and 0.45, respectively). Spatial variations in model performance were more stable for the CNN and combined models compared to the LUR models, suggesting that the combined approach may be less likely to contribute to differential exposure measurement error in epidemiological studies. In general, our findings demonstrated that satellite and street-level images can be combined with a traditional LUR modeling approach to improve predictions of within-city spatial variations in outdoor UFP and BC concentrations.

Modelling nationwide spatial variation of ultrafine particles based on mobile monitoring

BACKGROUND

Large nation- and region-wide epidemiological studies have provided important insights into the health effects of long-term exposure to outdoor air pollution. Evidence from these studies for the long-term effects of ultrafine particles (UFP), however is lacking. Reason for this is the shortage of empirical UFP land use regression models spanning large geographical areas including cities with varying topographies, peri-urban and rural areas. The aim of this paper is to combine targeted mobile monitoring and long-term regional background monitoring to develop national UFP models.

METHOD

We used an electric car to monitor UFP concentrations in selected cities and towns across the Netherlands over a 14-month period in 2016-2017. Routes were monitored 3 times and concentrations were averaged per road segment. In addition, we used kriging maps based on regional background monitoring (20 sites; 3 × 2 weeks) over the same period to assess annual average regional background concentrations. All road segments were used to model spatial variation of UFP with three different land-use (regression) approaches: supervised stepwise regression, LASSO and random forest. For each approach, we also tested a deconvolution method, which segregates the average concentration at each road segment into a local and background signal. Model performance was evaluated with short-term (400 sites across the Netherlands; 3 × 30 minutes) and external longer-term measurements (42 sites in two major cities; 3 × 24 hours). We also compared predictions of all six models at 1000 random addresses spread over the country.

RESULTS

We found similar predictive performance for the six models, with validation R² values from 0.25 to 0.35 for short-term measurements and 0.52 to 0.60 for longer-term external measurements. Models with and without deconvolution had similar predictive performance. All models based on the deconvolution method included a regional background kriging map as important predictor. Correlations between predictions at random addresses were high with Pearson correlations from 0.84 to 0.99. Models overestimated exposure at the short-term and long-term sites by about 20-30% in all cases, with small differences between regions and road types.

CONCLUSION

We developed robust nation-wide models for long-term UFP exposure combining mobile monitoring with long-term regional background monitoring. Minor differences in predictive performance between different algorithms were found, but the deconvolution approach is considered more physically realistic. The models will be applied in Dutch nation-wide health studies.

Measurement of harmful nanoparticle distribution among filters, smokers' respiratory systems, and surrounding air during cigarette smoking

This study was undertaken to investigate the filtration effect of filter on nanoparticle and the deposition behavior of nanoparticle in the human respiratory system from the aspect of nanoparticle number during cigarette smoking. For that, two kinds of experiments were designed. One is machine experiment, a well-controlled simulated respiratory system was designed to measure the raw emission and filter effect. Another is human experiment, volunteers were asked to inhale smoke into the oral cavity only and lungs, respectively, to distinguish smoke path. Results revealed that effective inhaled nanoparticle amount of a Taishan and a Hongtaishan cigarette were 5.8E + 9 (#) and 9.4E + 7 (#), respectively. The filter's integrated reduction rate was 41.65% for nanoparticle. For Taishan cigarette, 35.4% and 41.7% of raw emitted nanoparticles were deposited in the oral cavity and lungs, respectively, the rest of 22.9% was exhaled to surrounding air. The corresponding values were 25.6%, 41.5% and 32.9%, respectively, for Hongtaishan. The current findings are expected to provide basic assessments of filter effect and harm to human and to be a warning for smokers.

Shipping Remains a Globally Significant Source of Anthropogenic PN Emissions Even after 2020 Sulfur Regulation

Shipping is the main source of anthropogenic particle emissions in large areas of the globe, influencing climate, air quality, and human health in open seas and coast lines. Here, we determined, by laboratory and on-board measurements of ship engine exhaust, fuel-specific particle number (PN) emissions for different fuels and desulfurization applied in shipping. The emission factors were compared to ship exhaust plume observations and, furthermore, exploited in the assessment of global PN emissions from shipping, utilizing the STEAM ship emission model. The results indicate that most particles in the fresh ship engine exhaust are in ultrafine particle size range. Shipping PN emissions are localized, especially close to coastal lines, but significant emissions also exist on open seas and oceans. The global annual PN produced by marine shipping was 1.2 × 10²⁸ (±0.34 × 10²⁸) particles in 2016, thus being of the same magnitude with total anthropogenic PN emissions in continental areas. The reduction potential of PN from shipping strongly depends on the adopted technology mix, and except wide adoption of natural gas or scrubbers, no significant decrease in global PN is expected if heavy fuel oil is mainly replaced by low sulfur residual fuels. The results imply that shipping remains as a significant source of anthropogenic PN emissions that should be considered in future climate and health impact models.

Reductions in traffic-related black carbon and ultrafine particle number concentrations in an urban neighborhood during the COVID-19 pandemic

We investigated changes in traffic-related air pollutant concentrations in an urban area during the COVID-19 pandemic. The study was conducted in a mixed commercial-residential neighborhood in Somerville (MA, USA), where traffic is the dominant source of air pollution. Measurements were made between March 27 and May 14, 2020, coinciding with a dramatic reduction in traffic (71% drop in car and 46% drop in truck traffic) due to business shutdowns and a statewide stay-at-home advisory. Indicators of fresh vehicular emissions (ultrafine particle number concentration [PNC] and black carbon [BC]) were measured with a mobile monitoring platform on an interstate highway and major and minor roadways. Our results show that depending on road class, median PNC and BC contributions from traffic were 60-68% and 22-46% lower, respectively, during the lockdown compared to pre-pandemic conditions, and corresponding reductions in total on-road concentrations were 45-69% and 22-56%, respectively. A higher BC: PNC concentration ratio was observed during the lockdown period likely indicative of the higher fraction of diesel vehicles in the fleet during the lockdown. Overall, the scale of reductions in ultrafine particle and BC concentrations was commensurate with the reductions in traffic. This natural experiment allowed us to quantify the direct impacts of reductions in traffic emissions on neighborhood-scale air quality, which are not captured by the regional regulatory-monitoring network. These results underscore the importance of measurements of appropriate proxies for traffic emissions at relevant spatial scales. Our results are useful for exposure analysis as well as city and regional planners evaluating mitigation strategies for traffic-related air pollution.